US dataswitch to UK
Tax Preparers
computing taxes owed or overpaid, preparing or assisting in preparing simple to complex tax returns for individuals or small businesses and reviewing financial records. If that's your week, this page is about your job.
The honest answer
Most tasks in this job are the kind AI has learned to do: computing taxes owed or overpaid. The tasks, though, are not you.
It would be a lie to soften that; interviewing clients to obtain additional information on taxable income and deductible expenses and allowances is what this work rebuilds around. The plan below starts there.
Your week, as this page understands it
Prepare tax returns for individuals or small businesses. The job title says “tax preparers”. The real job is the part underneath: interviewing clients to obtain additional information on taxable income and deductible expenses and allowances. That is the thing someone has to be right about.
The exposed part of this job is specific, and we won’t pretend it is coming back. But tax preparers is not one task. It is 12 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is interviewing clients to obtain additional information on taxable income and deductible expenses and allowances, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 56%
- changing shape
- 44%
- staying human
- 0%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 65 out of 100 (60–70 allowing for uncertainty): high exposure, across 12 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.
How we know this
What is measured: Every published task statement for tax preparers is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.
How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.
Release: 2026-q4.1, scores computed 2026-08-04. Read the full method.
Your job, task by task
These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.
- 1 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
Shifting to AI
7 tasksTasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.
Computing taxes owed or overpaid
This is reading one thing and writing another: taxes in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Compute taxes owed or overpaid, using adding machines or personal computers, and complete entries on forms, following tax form instructions and tax tables.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Working out the tax owed from the figures is arithmetic against published tables, which software already does reliably.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Reviewing financial records
This is reading one thing and writing another: financial records in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Review financial records, such as income statements and documentation of expenditures to determine forms needed to prepare tax returns.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (62–70 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Reading income statements and receipts to decide which forms are needed is document work with clear rules.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Explaining federal and state tax laws to individuals and companies
This is reading one thing and writing another: federal in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Explain federal and state tax laws to individuals and companies.” (O*NET task statement)
How this row was scored
Exposure score: 61 out of 100 (57–65 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Tax law is published in enormous detail, so clear explanations can be generated and only lightly checked.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.
Consulting tax law handbooks or bulletins to determine procedures for preparation of atypical returns
This is reading one thing and writing another: tax law handbooks in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Consult tax law handbooks or bulletins to determine procedures for preparation of atypical returns.” (O*NET task statement)
How this row was scored
Exposure score: 72 out of 100 (68–76 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Looking up handbooks and bulletins for an unusual return is searching published material, something AI does quickly and well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Checking data input or verifying totals on forms prepared by others to detect errors in arithmetic
This is reading one thing and writing another: data input in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Check data input or verify totals on forms prepared by others to detect errors in arithmetic, data entry, or procedures.” (O*NET task statement)
How this row was scored
Exposure score: 88 out of 100 (84–92 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Re-checking another person's sums and entries for mistakes is exactly the kind of checking machines do best.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Changing shape
5 tasksTasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.
Using all appropriate adjustments, deductions and credits to keep clients' taxes to a minimum
The software now makes the first pass at all appropriate adjustments, deductions and credits, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 5 · CoreSource: “Use all appropriate adjustments, deductions, and credits to keep clients' taxes to a minimum.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (52–60 allowing for uncertainty): partial exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Spotting the deductions and credits that apply follows written rules, though a paid preparer still signs off on the choices.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Furnishing taxpayers with sufficient information and advice to ensure correct tax form completion
The software now makes the first pass at taxpayers, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 5 · CoreSource: “Furnish taxpayers with sufficient information and advice to ensure correct tax form completion.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (41–55 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Explaining what a taxpayer must supply is well-documented guidance, but a responsible preparer usually delivers it personally.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Interviewing clients to obtain additional information on taxable income and deductible expenses and allowances
The software now makes the first pass at clients, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 5 · CoreSource: “Interview clients to obtain additional information on taxable income and deductible expenses and allowances.” (O*NET task statement)
How this row was scored
Exposure score: 46 out of 100 (39–53 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Guided questionnaires already collect income and expense details, though many clients open up more with a person asking.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Preparing or assisting in preparing simple to complex tax returns for individuals or small businesses
The software now makes the first pass at preparing simple, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 5 · CoreSource: “Prepare or assist in preparing simple to complex tax returns for individuals or small businesses.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (52–60 allowing for uncertainty): partial exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Return software plus AI drafts most returns well, but a qualified preparer signs and owns the filing.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Answering questions and providing future tax planning to clients
The software now makes the first pass at questions, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Answer questions and provide future tax planning to clients.” (O*NET task statement)
How this row was scored
Exposure score: 46 out of 100 (39–53 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Planning answers can be drafted from the rules, but clients weigh advice partly on who is giving it.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Staying human
0 tasksTasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.
Nothing in this job’s scored task list landed in this group. That is the measurement, not an editorial choice, and it is worth knowing either way.
Show the other 2 tasks
Calculating form preparation fees according to return complexity and processing time
shifting to AIThis is reading one thing and writing another: form preparation fees in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Calculate form preparation fees according to return complexity and processing time required.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Working out a fee from complexity and time is simple arithmetic against a price list.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Scheduling appointments with clients
shifting to AIThis is reading one thing and writing another: appointments in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Schedule appointments with clients.” (O*NET task statement)
How this row was scored
Exposure score: 85 out of 100 (81–89 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Booking client appointments is standard scheduling software work with only a brief, routine exchange involved.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.
What this job pays, and how many people do it
- Median pay
- $54,920a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
- People doing this job
- 76,480in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)
What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.
Why this is shifting
The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: financial records in, a record out. The rows above are exactly that shape: computing taxes owed or overpaid and reviewing financial records. What it cannot do is be trusted in person, which is what clients run on: someone specific doing it and standing behind it. Which is why this page talks about your tasks changing, not your job ending.
Your move
Over a pint: what I’d tell you if you were my friend
The exposed part of your job is the biggest part, and I am not going to dress that up: computing taxes owed or overpaid is work today's tools do quickly and cheaply, and that is not coming back.
So, given all that: 56% of this job's task weight sits in rows the software is already learning, 44% in rows that change shape rather than disappear, and 0% in rows it is nowhere near. That is the position, measured across 12 scored tasks. It is not a forecast about you.
What you have that the software does not is interviewing clients to obtain additional information on taxable income and deductible expenses and allowances, plus the years of knowing when something looks wrong before you can say why. That is the raw material for everything below.
This week: one thing
Sit on the machine's side of the desk. Pick one real piece of financial records you would normally do yourself, let whatever software you already have take the first pass at it, and then go through what it produced and write down every single thing it got wrong. One evening this week. Do not fix anything yet. Just catch it.
- What you end up holding
- a written list of the machine’s mistakes, in your handwriting
- How long it takes
- an evening, or an hour if you pick one job rather than one client
If you can’t run software on your employer’s or your clients’ data: Do the same hunt on paper. Take one printed piece of financial records, work through it the way you always do, and mark every point where you made a call rather than followed a rule. Same evening, same list, nothing to log into and nobody to ask permission from. That list is the same artifact: it is the judgment written down.
Over the next 90 days
Change one sentence about what you do. Not on a CV. Out loud, to whoever pays you. From “my job is computing taxes owed or overpaid” to “I check what the software does and tell you what it means.” Your error list from this week is what makes that sentence true instead of a claim, so use it: show it once, to one person, inside the next ninety days. Same skills, priced as judgment rather than as typing.
Over the next 12 months
Walk toward the end of this job that answers for things, and get it recognised. Pick the one part of interviewing clients to obtain additional information on taxable income and deductible expenses and allowances you are already best at, and spend the year making it formal: a qualification, a named responsibility, a specialism people ask for by name. Price it honestly: that is evenings, it is months rather than weeks, and the seats are competitive because everyone in your position is looking at the same door. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.
The roads out of here, and why I am not sending you down them
I looked at the obvious moves out of this job, and here is what I found.
I checked the 12 nearest US occupations to tax preparers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was personal financial advisors: only about 6% of its durable work is work you already do. I am not going to pretend that is comfortable news: 56% of your own task list is already in the top exposure band. But the answer on this evidence is not a sideways jump into a job with the same problem. It is to walk toward the end of this one that answers for things. “use all appropriate adjustments, deductions, and credits to keep clients' taxes to…” is the part that stays with a person, and spending a year getting formally recognised for it beats a standing start somewhere else.
How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.
3 moves I checked and rejected
These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.
Personal Financial Advisors
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already answer questions and provide future tax planning to clients, and their equivalent is to answer clients' questions about the purposes and details of financial plans and strategies. Across both published task lists that is about 6% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 6% of the durable side of that job. That is a different job, not a next step.
Tax Examiners and Collectors, and Revenue Agents
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already explain federal and state tax laws to individuals and companies, and their equivalent is to collect taxes from individuals or businesses according to prescribed laws and regulations. Across both published task lists that is about 5% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 5% of the durable side of that job. That is a different job, not a next step.
Mental Health and Substance Abuse Social Workers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already schedule appointments with clients, and their equivalent is to assist clients in adhering to treatment plans. Across both published task lists that is about 3% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 3% of the durable side of that job. That is a different job, not a next step.
What I’d stop worrying about
A friend tells you what not to spend fear on. This is that list.
The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 56% of its task weight, across 12 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
“It’s too late for me to become something else”
You are not starting from zero, and the page shows why: interviewing clients to obtain additional information on taxable income and deductible expenses and allowances is work the software cannot do and you already do it. The move above is a repricing of what you know, not a new career. Nobody who has just left college has that.
“I should learn to code”
Almost certainly not. The value in your job is moving toward checking, deciding and answering for the output, not toward writing the software. A weekend of Python will not change your position; the error list from this week will.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.
You are reading the United States figures
The United Kingdom splits this work across more than one official group, of which Taxation experts is the closest. The pay and employment figures are not directly comparable, and we do not average them together.
Switch to the United Kingdom page →partial match
The other groups this work is counted across:
In UK official statistics this job is counted as Taxation experts and Chartered and certified accountants. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.
Your route through this
Where to go next, and what it costs
Free, and complete
The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.
Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
Free
No Space for this job, but one for what is happening to it
Nothing Collab365 runs is built for tax preparers, and we are not going to point you at the nearest one and call it a fit.
There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 56% of the work on this page is already inside what they can do.
7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.
The AI Authority is a general community about working with AI, not a course for tax preparers. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.
Noted, and thank you. We’ll email you if a Space for tax preparers launches. Nothing else.
That did not look like an email address, so nothing was saved. Have another go below.
We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.
No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.
Questions people ask about this job
- Will AI replace Tax Preparers?
- Not as a job, but it is already doing parts of the work. Across the 12 official task statements scored for Tax Preparers (United States, SOC 13-2082), 56% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 65 out of 100 (range 60–70, band: high). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
- Which tasks in “Tax Preparers” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Calculate form preparation fees according to return complexity and processing time required” (93/100, very high); “Check data input or verify totals on forms prepared by others to detect errors in arithmetic, data entry, or procedures” (88/100, very high); “Schedule appointments with clients” (85/100, very high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
- Which tasks in “Tax Preparers” stay human?
- About 0% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Answer questions and provide future tax planning to clients” (46/100, partial); “Interview clients to obtain additional information on taxable income and deductible expenses and allowances” (46/100, partial); “Furnish taxpayers with sufficient information and advice to ensure correct tax form completion” (48/100, partial). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
- What should someone working in “Tax Preparers” do about AI?
- Start from the ledger rather than the headline: 56% of this job's weighted core work is exposed, and roughly 0% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
- How is the AI exposure score for Tax Preparers calculated?
- Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 12 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.
Where these numbers come from
Worth knowing about these figures
- The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
- 1 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
- Task statements
- onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
- Task weights
- onet-db (im-rt)
- Scores
- Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-04.
- Pay and employment
- bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))
Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.
The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.
The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.
Using these figures?
Cite this
Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.
Plain text
Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).
BibTeX
@misc{collab365futureproof2026q41,
title = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
author = {{Collab365}},
year = {2026},
url = {https://futureproof.collab365.com/data/2026-q4.1},
note = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}Data as of release 2026-q4.1, published . Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.